Courses

MIT Arti?cal Intelligence Videos — MIT AI Course
Grokking Deep Learning in Motion — Beginner’s course to learn deep learning and neural networks without frameworks.
Intro to Artificial Intelligence — Learn the Fundamentals of AI.Course run by Peter Norvig
EdX Arti?cial Intelligence— The course will introduce the basic ideas and techniques underlying the design of intelligent computer systems
Arti?cial Intelligence For Robotics — This class will teach you basic methods in Arti?cial Intelligence, including: probabilistic inference, planning and search, localization, tracking and control,
all with a focus on robotics
Machine Learning— Basic machine learning algorithms for supervised and unsupervised learning
Neural Networks For Machine Learning — Algorithmic and practical tricks for arti?cal neural networks.
Deep Learning— An Introductory course to the world of Deep Learning.
Stanford Statistical Learning — Introductory course on machine learning focusing on: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting;support-vector machines.
Knowledge Based Arti?cial Intelligence — Georgia Tech’s course on Articial Intelligence focussing on Symbolic AI.
Deep RL Bootcamp Lectures — Deep Reinforcement Bootcamp Lectures — August 2017



Books


Artificial Intelligence: A Modern Approach — Stuart Russell &Peter Norvig Also consider browsing the list of recommended reading, divided
by each chapter in “Arti?cial Intelligence: A Modern Approach”.
Paradigms Of Arti?cial Intelligence Programming: Case Studies in
Common Lisp — Paradigms of AI Programming is the ?rst text to teach advanced Common Lisp techniques in the context of
building major AI systems
Reinforcement Learning: An Introduction — This introductory textbook on reinforcement learning is targeted toward engineers and scientists in arti?cial intelligence, operations research, neural networks, and control systems, and we hope it will also be of interest to psychologists and neuroscientists.
The Cambridge Handbook Of Arti?cial Intelligence — Written for non-specialists, it covers the discipline’s foundations, major
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theories, and principal research areas, plus related topics such as artificial life
The Emotion Machine: Commonsense Thinking, Arti?cial
Intelligence, and the Future of the Human Mind — In this mind-
expanding book, scienti?c pioneer Marvin Minsky continues his
groundbreaking research, o?ering a fascinating new model for
how our minds work
Arti?cial Intelligence: A New Synthesis— Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI
On Intelligence— Hawkins develops a powerful theory of how the human brain works, explaining why computers are not intelligent and how, based on this new theory, we can ?nally build intelligent machines. Also audio version available from audible.com
How To Create A Mind— Kurzweil discusses how the brain works,how the mind emerges, brain-computer interfaces, and the implications of vastly increasing the powers of our intelligence toaddress the world’s problems
Deep Learning — Goodfellow, Bengio and Courville’s introductionto a broad range of topics in deep learning, covering mathematical
and conceptual background, deep learning techniques used in industry, and research perspectives.
The Elements of Statistical Learning: Data Mining, Inference, and
Prediction — Hastie and Tibshirani cover a broad range of topics,
from supervised learning (prediction) to unsupervised learning
including neural networks, support vector machines, classi?cation
trees and boosting — -the ?rst comprehensive treatment of this
topic in any book.
Deep Learning and the Game of Go — Deep Learning and the
Game of Go teaches you how to apply the power of deep learning
to complex human-?avored reasoning tasks by building a Go-
playing AI. After exposing you to the foundations of machine and
deep learning, you’ll use Python to build a bot and then teach it
the rules of the game.
Deep Learning for Search — Deep Learning for Search teaches you
how to leverage neural networks, NLP, and deep learning
techniques to improve search performance.
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Deep Learning with PyTorch — PyTorch puts these superpowers in
your hands, providing a comfortable Python experience that gets
you started quickly and then grows with you as you — and your
deep learning skills — become more sophisticated. Deep Learning
with PyTorch will make that journey engaging and fun.
Deep Reinforcement Learning in Action — Deep Reinforcement
Learning in Action teaches you the fundamental concepts and
terminology of deep reinforcement learning, along with the
practical skills and techniques you’ll need to implement it into
your own projects.
Grokking Deep Reinforcement Learning— Grokking Deep
Reinforcement Learning introduces this powerful machine
learning approach, using examples, illustrations, exercises, and
crystal-clear teaching.



Programming


Prolog Programming For Arti?cial Intelligence — This best-selling
guide to Prolog and Arti?cial Intelligence concentrates on the art
of using the basic mechanisms of Prolog to solve interesting AI
problems.
AI Algorithms, Data Structures and Idioms in Prolog, Lisp and
Java — PDF here
Python Tools for Machine Learning
Python for Arti?cial Intelligence

Philosophy


Super Intelligence — Superintelligence asks the questions: What happens when machines surpass humans in general intelligence. A
really great book.
Our Final Invention: Arti?cial Intelligence And The End Of The
Human Era — Our Final Invention explores the perils of the heedless pursuit of advanced AI. Until now, human intelligence has had no rival. Can we coexist with beings whose intelligence dwarfs our own? And will they allow us to?
How to Create a Mind: The Secret of Human Thought Revealed —Ray Kurzweil, director of engineering at Google, explored the process of reverse-engineering the brain to understand precisely
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